リソース詳細 · 图片与视频
Diffusers 项目导览
了解图像、视频生成管线如何连接模型与推理环境。
本文・例・ライセンスは原文のままです。コードを表示するだけで、オンライン実行やAI呼び出しは行いません。
リソース詳細
适合有 Python 基础、希望了解本地生成工具组成的开发者。它是模型管线库，不附带所有生成模型，也不是即开即用的视频网站。
始める前に
- 対応環境
- 依环境确认
- 更新日
- 官方安装页目前要求 Python 3.10+，并以 PyTorch 2.6+ 测试；按自己系统核对 PyTorch 与硬件后端。
- 另行准备许可适用的模型及足够内存、显存和存储；图像与视频管线的资源要求不同。
本站未安装实测，不提供未经实测的一键命令；先按官方安装页选择设备与模型，再从小图测试开始。
よくある注意点
- Windows 先核对缓存与模型下载目录，避免默认占用系统盘；不能把文档中的 cuda 直接套到所有设备。
- 模型权重与素材许可独立，部分模型需接受额外条款；离线运行也需要先备齐文件，托管推理费用另算。
本文全文
【可以做什么】把选定的生成模型、调度器和推理步骤组合为图像或视频工作流。先研究一条简单图像管线，再考虑更耗资源的视频任务。
【开始前准备】按官方安装页选择受支持的 Python 与 PyTorch 环境，再核对设备后端、可用内存和显存。另行阅读所选模型的模型卡、授权条款和文件大小；不要将库的 Apache-2.0 视为每个模型都允许商用或分发。
【第一次尝试】用原创、简单的画面描述，在独立环境处理一张低负载测试图。记录模型版本、种子、分辨率和资源用量，比较同一配置下的结果。
【检查结果】能成功出图不代表角色一致性、作品权利或视频流畅度已经解决。Windows 下先确认缓存目录，避免模型默认下载到系统盘；官方示例中的 cuda 也需按实际设备调整。
【来源与许可】huggingface 官方仓库 main 分支，固定提交 73faca368c0da77645ea58836aa8780d2d8c5353，提交日期 2026-10-22；主仓库采用 Apache-2.0，完整条款原样保留。
【核验范围】2026-10-22 阅读官方仓库、固定提交的 README 与完整 LICENSE，并核对官方安装说明；核对时仓库未归档。本站只提供原创导览，不提供上游源码下载。上游许可全文仅供核对，不表示本站完成了安全审计；本站未安装实测该项目，不保证各设备或未来版本兼容。工具许可不等于模型权重、数据集、声音、图像素材、插件、依赖或企业服务的许可，需要分别核对。模型、云 API 与托管服务可能收费，硬件、存储与部署也有成本。使い方
この項目はプロジェクト案内で、独立した三段階の練習はまだありません。本文・前提条件・注意点を読み、公式ガイドに従ってください。上流プロジェクトのインストールや検証を実施したという意味ではありません。
作者と出典
- クレジット
- 本站导览
- 上流の作者
- huggingface（官方仓库维护组织）
- 出典バージョン
73faca368c0da77645ea58836aa8780d2d8c5353- ライセンス確認日
- 2026-10-22
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资料与许可已核对
只核对项目资料和许可记录；未安装运行上游项目，也未进行安全审计。
2026-10-22